## Loading required package: ggplot2
## Loading required package: reshape2
# importing our data
data = data.import()
## Warning in if (is.na(value)) name = "NA" else if (value >= 348.75 || value
## <= : the condition has length > 1 and only the first element will be used
head(data)
Overview
summary(data)
## dtPosix dt
## Min. :2017-01-01 00:00:00 Min. :1.483e+09
## 1st Qu.:2017-04-01 10:45:00 1st Qu.:1.491e+09
## Median :2017-07-03 15:30:00 Median :1.499e+09
## Mean :2017-07-03 03:05:03 Mean :1.499e+09
## 3rd Qu.:2017-10-04 02:15:00 3rd Qu.:1.507e+09
## Max. :2017-12-31 23:00:00 Max. :1.515e+09
## NA's :37
## dt_iso city_id temp
## 2017-03-18 06:00:00 +0000 UTC: 3 Min. :2950159 Min. :263.1
## 2017-03-30 01:00:00 +0000 UTC: 3 1st Qu.:2950159 1st Qu.:277.1
## 2017-03-30 02:00:00 +0000 UTC: 3 Median :2950159 Median :283.1
## 2017-03-30 03:00:00 +0000 UTC: 3 Mean :2950159 Mean :283.4
## 2017-03-30 04:00:00 +0000 UTC: 3 3rd Qu.:2950159 3rd Qu.:289.1
## (Other) :9104 Max. :2950159 Max. :305.1
## NA's : 37 NA's :37 NA's :37
## temp_min temp_max pressure humidity
## Min. :261.1 Min. :263.7 Min. : 980 Min. : 14.00
## 1st Qu.:277.1 1st Qu.:277.4 1st Qu.:1010 1st Qu.: 67.00
## Median :283.1 Median :283.1 Median :1016 Median : 81.00
## Mean :283.0 Mean :283.7 Mean :1015 Mean : 77.17
## 3rd Qu.:289.1 3rd Qu.:289.1 3rd Qu.:1021 3rd Qu.: 93.00
## Max. :305.1 Max. :305.1 Max. :1043 Max. :100.00
## NA's :37 NA's :37 NA's :37 NA's :37
## wind_speed wind_deg rain_3h clouds_all
## Min. : 0.00 Min. : 0.0 Min. :0.118 Min. : 0.00
## 1st Qu.: 2.00 1st Qu.:120.0 1st Qu.:0.150 1st Qu.: 0.00
## Median : 3.00 Median :230.0 Median :0.380 Median : 75.00
## Mean : 3.43 Mean :197.5 Mean :0.672 Mean : 45.13
## 3rd Qu.: 5.00 3rd Qu.:270.0 3rd Qu.:0.889 3rd Qu.: 75.00
## Max. :14.00 Max. :360.0 Max. :9.865 Max. :100.00
## NA's :37 NA's :37 NA's :9066 NA's :37
## weather_id weather_main weather_description weather_icon
## Min. :200.0 Clouds :3434 Sky is Clear :2972 01n :1593
## 1st Qu.:701.0 Clear :2973 broken clouds :2380 04d :1390
## Median :800.0 Rain :1195 light rain : 803 01d :1379
## Mean :728.3 Mist : 598 mist : 598 04n :1171
## 3rd Qu.:803.0 Fog : 383 scattered clouds: 536 50n : 673
## Max. :804.0 (Other): 536 (Other) :1830 (Other):2913
## NA's :37 NA's : 37 NA's : 37 NA's : 37
## weekday hours chb.all chb.background
## sun :1331 4 : 392 Min. :0.2000 Min. :0.1000
## wed :1316 6 : 392 1st Qu.:0.6667 1st Qu.:0.5000
## fri :1314 1 : 391 Median :0.9333 Median :0.7000
## thu :1303 3 : 390 Mean :1.1730 Mean :0.9167
## tue :1290 2 : 389 3rd Qu.:1.3667 3rd Qu.:1.1000
## (Other):2565 (Other):7165 Max. :8.9000 Max. :9.8000
## NA's : 37 NA's : 37 NA's :1 NA's :162
## chb.traffic cht.all cht.background cht.traffic
## Min. :0.200 Min. : 0.000 Min. : 0.00 Min. : 0.000
## 1st Qu.:0.750 1st Qu.: 1.333 1st Qu.: 1.00 1st Qu.: 1.500
## Median :1.050 Median : 2.000 Median : 1.00 Median : 2.500
## Mean :1.303 Mean : 2.483 Mean : 1.81 Mean : 2.819
## 3rd Qu.:1.550 3rd Qu.: 3.000 3rd Qu.: 2.00 3rd Qu.: 3.500
## Max. :9.400 Max. :19.667 Max. :24.00 Max. :18.500
## NA's :9 NA's :1 NA's :161 NA's :4
## co.all co.traffic no2.all no2.background
## Min. :0.1000 Min. :0.1000 Min. : 3.929 Min. : 4.00
## 1st Qu.:0.2667 1st Qu.:0.2667 1st Qu.: 19.750 1st Qu.: 15.40
## Median :0.3500 Median :0.3500 Median : 27.625 Median : 22.40
## Mean :0.3867 Mean :0.3867 Mean : 29.279 Mean : 25.35
## 3rd Qu.:0.4500 3rd Qu.:0.4500 3rd Qu.: 36.806 3rd Qu.: 32.60
## Max. :2.2500 Max. :2.2500 Max. :144.062 Max. :171.40
## NA's :1 NA's :1 NA's :1 NA's :1
## no2.traffic no2.suburb no.all no.background
## Min. : 4.00 Min. : 1.20 Min. : 0.4375 Min. : 0.000
## 1st Qu.: 31.00 1st Qu.: 6.60 1st Qu.: 6.4375 1st Qu.: 1.250
## Median : 44.83 Median :10.80 Median : 13.0000 Median : 2.800
## Mean : 45.88 Mean :12.94 Mean : 17.8855 Mean : 6.473
## 3rd Qu.: 58.33 3rd Qu.:17.00 3rd Qu.: 23.0000 3rd Qu.: 6.000
## Max. :187.67 Max. :66.40 Max. :273.3125 Max. :361.800
## NA's :1 NA's :1 NA's :1 NA's :1
## no.traffic no.suburb nox.all nox.background
## Min. : 1.167 Min. : 0.000 Min. : 6.00 Min. : 5.20
## 1st Qu.: 15.333 1st Qu.: 0.200 1st Qu.: 30.69 1st Qu.: 18.20
## Median : 31.143 Median : 0.400 Median : 48.27 Median : 27.00
## Mean : 40.297 Mean : 1.783 Mean : 56.59 Mean : 35.22
## 3rd Qu.: 53.500 3rd Qu.: 1.200 3rd Qu.: 71.00 3rd Qu.: 41.60
## Max. :419.667 Max. :90.000 Max. :561.44 Max. :723.80
## NA's :1 NA's :1 NA's :1 NA's :1
## nox.traffic nox.suburb o3.all o3.background
## Min. : 7.833 Min. : 1.60 Min. : 0.50 Min. : 0.00
## 1st Qu.: 55.333 1st Qu.: 7.00 1st Qu.: 24.17 1st Qu.: 20.00
## Median : 94.000 Median : 11.60 Median : 42.50 Median : 38.50
## Mean :107.422 Mean : 15.66 Mean : 44.07 Mean : 40.46
## 3rd Qu.:140.333 3rd Qu.: 19.25 3rd Qu.: 60.67 3rd Qu.: 57.50
## Max. :828.500 Max. :189.20 Max. :142.67 Max. :138.00
## NA's :1 NA's :1 NA's :1 NA's :2
## o3.traffic o3.suburb pm10.all pm10.background
## Min. : 1.0 Min. : 0.25 Min. : 4.00 Min. : 3.333
## 1st Qu.:11.0 1st Qu.: 25.62 1st Qu.: 13.91 1st Qu.: 12.667
## Median :25.0 Median : 45.00 Median : 18.82 Median : 17.667
## Mean :24.3 Mean : 45.94 Mean : 22.70 Mean : 21.351
## 3rd Qu.:35.0 3rd Qu.: 63.00 3rd Qu.: 27.70 3rd Qu.: 26.333
## Max. :72.0 Max. :145.00 Max. :283.73 Max. :211.667
## NA's :8469 NA's :1 NA's :1 NA's :1
## pm10.traffic pm10.suburb so2.all so2.background
## Min. : 5.00 Min. : 3.00 Min. : 0.000 Min. : 0.000
## 1st Qu.: 16.80 1st Qu.: 10.00 1st Qu.: 0.500 1st Qu.: 0.000
## Median : 22.40 Median : 14.00 Median : 1.000 Median : 1.000
## Mean : 26.68 Mean : 17.29 Mean : 1.522 Mean : 1.198
## 3rd Qu.: 32.20 3rd Qu.: 21.33 3rd Qu.: 1.500 3rd Qu.: 1.000
## Max. :465.40 Max. :106.33 Max. :356.000 Max. :27.000
## NA's :1 NA's :1 NA's :4 NA's :27
## so2.traffic wind.deg.name
## Min. : 0.000 Length:9156
## 1st Qu.: 1.000 Class :character
## Median : 1.000 Mode :character
## Mean : 1.844
## 3rd Qu.: 2.000
## Max. :699.000
## NA's :54
pm10 over the year
pollutant = "pm10.all"
plot.pollutant(data, pollutant, month = "01", day = "01", title = "1. January with silvester firework peak")

plot.pollutant(data, pollutant, month = "01")

plot.pollutant(data, pollutant, month = "02")

plot.pollutant(data, pollutant, month = "03")

plot.pollutant(data, pollutant, month = "04")

plot.pollutant(data, pollutant, month = "05")

plot.pollutant(data, pollutant, month = "06")

plot.pollutant(data, pollutant, month = "07")

plot.pollutant(data, pollutant, month = "08")

plot.pollutant(data, pollutant, month = "09")

plot.pollutant(data, pollutant, month = "10")

plot.pollutant(data, pollutant, month = "11")

plot.pollutant(data, pollutant, month = "12")

chb over the year
pollutant = "chb.all"
plot.pollutant(data, pollutant, month = "01", day = "01", title = "1. January with silvester firework peak")

plot.pollutant(data, pollutant, month = "01")

plot.pollutant(data, pollutant, month = "02")

plot.pollutant(data, pollutant, month = "03")

plot.pollutant(data, pollutant, month = "04")

plot.pollutant(data, pollutant, month = "05")

plot.pollutant(data, pollutant, month = "06")

plot.pollutant(data, pollutant, month = "07")

plot.pollutant(data, pollutant, month = "08")

plot.pollutant(data, pollutant, month = "09")

plot.pollutant(data, pollutant, month = "10")

plot.pollutant(data, pollutant, month = "11")

plot.pollutant(data, pollutant, month = "12")

CHT over the year
pollutant = "cht.all"
plot.pollutant(data, pollutant, month = "01")

plot.pollutant(data, pollutant, month = "02")

plot.pollutant(data, pollutant, month = "03")

plot.pollutant(data, pollutant, month = "04")

plot.pollutant(data, pollutant, month = "05")

plot.pollutant(data, pollutant, month = "06")

plot.pollutant(data, pollutant, month = "07")

plot.pollutant(data, pollutant, month = "08")

plot.pollutant(data, pollutant, month = "09")

plot.pollutant(data, pollutant, month = "10")

plot.pollutant(data, pollutant, month = "11")

plot.pollutant(data, pollutant, month = "12")

CO over the year
pollutant = "co.all"
plot.pollutant(data, pollutant, month = "01", day = "01", title = "1. January with silvester firework peak")

plot.pollutant(data, pollutant, month = "01")

plot.pollutant(data, pollutant, month = "02")

plot.pollutant(data, pollutant, month = "03")

plot.pollutant(data, pollutant, month = "04")

plot.pollutant(data, pollutant, month = "05")

plot.pollutant(data, pollutant, month = "06")

plot.pollutant(data, pollutant, month = "07")

plot.pollutant(data, pollutant, month = "08")

plot.pollutant(data, pollutant, month = "09")

plot.pollutant(data, pollutant, month = "10")

plot.pollutant(data, pollutant, month = "11")

plot.pollutant(data, pollutant, month = "12")

5. NOX over the year
pollutant = "nox.all"
plot.pollutant(data, pollutant, month = "01", day = "01", title = "1. January with silvester firework peak")

plot.pollutant(data, pollutant, month = "01")

plot.pollutant(data, pollutant, month = "02")

plot.pollutant(data, pollutant, month = "03")

plot.pollutant(data, pollutant, month = "04")

plot.pollutant(data, pollutant, month = "05")

plot.pollutant(data, pollutant, month = "06")

plot.pollutant(data, pollutant, month = "07")

plot.pollutant(data, pollutant, month = "08")

plot.pollutant(data, pollutant, month = "09")

plot.pollutant(data, pollutant, month = "10")

plot.pollutant(data, pollutant, month = "11")

plot.pollutant(data, pollutant, month = "12")

6. O3 over the year
pollutant = "o3.all"
plot.pollutant(data, pollutant, month = "01")

plot.pollutant(data, pollutant, month = "02")

plot.pollutant(data, pollutant, month = "03")

plot.pollutant(data, pollutant, month = "04")

plot.pollutant(data, pollutant, month = "05")

plot.pollutant(data, pollutant, month = "06")

plot.pollutant(data, pollutant, month = "07")

plot.pollutant(data, pollutant, month = "08")

plot.pollutant(data, pollutant, month = "09")

plot.pollutant(data, pollutant, month = "10")

plot.pollutant(data, pollutant, month = "11")

plot.pollutant(data, pollutant, month = "12")

pm10 over the year
pollutant = "so2.all"
plot.pollutant(data, pollutant, month = "01", day = "01", title = "1. January with silvester firework peak")

plot.pollutant(data, pollutant, month = "01")

plot.pollutant(data, pollutant, month = "02")

plot.pollutant(data, pollutant, month = "03")

plot.pollutant(data, pollutant, month = "04")

plot.pollutant(data, pollutant, month = "05")

plot.pollutant(data, pollutant, month = "06")

plot.pollutant(data, pollutant, month = "07")

plot.pollutant(data, pollutant, month = "08")

plot.pollutant(data, pollutant, month = "09")

plot.pollutant(data, pollutant, month = "10")

plot.pollutant(data, pollutant, month = "11")

plot.pollutant(data, pollutant, month = "12")

pm10 to wind
ddply(data,~wind_speed,summarise,pm10.all.mean=mean(pm10.all),sd=sd(pm10.all))
ggplot(data, aes(wind_speed,pm10.all, group = wind_speed)) + geom_boxplot() + ylim(0, 70) + stat_summary(fun.y=mean, colour="darkred", geom="point")
## Warning: Removed 37 rows containing missing values (stat_boxplot).
## Warning: Removed 76 rows containing non-finite values (stat_boxplot).
## Warning: Removed 113 rows containing non-finite values (stat_summary).

ddply(data,~wind.deg.name,summarise,pm10.all.mean=mean(pm10.all),sd=sd(pm10.all))
ggplot(data, aes(wind.deg.name,pm10.all, group = wind.deg.name)) + geom_boxplot() + ylim(0, 70) + stat_summary(fun.y=mean, colour="darkred", geom="point")
## Warning: Removed 80 rows containing non-finite values (stat_boxplot).
## Warning: Removed 80 rows containing non-finite values (stat_summary).

ddply(data,~wind.deg.name,summarise,wind_speed.mean=mean(wind_speed),sd=sd(wind_speed))
ggplot(data, aes(wind.deg.name,wind_speed, group = wind.deg.name)) + geom_boxplot() + ylim(0, 15) + stat_summary(fun.y=mean, colour="darkred", geom="point")
## Warning: Removed 37 rows containing non-finite values (stat_boxplot).
## Warning: Removed 37 rows containing non-finite values (stat_summary).
